Keywords

Abstract

The effective application of a data mining process is
littered with many difficult and technical decisions (i.e.
data cleansing, feature transformations, algorithms,
parameters, evaluation). Subsequently, most data mining
products provide a large number of models and tools, but
few provide intelligent assistance for addressing the
above-mentioned challenges that face the non-specialist
data miner. In this paper, we propose the realization of a
hybrid intelligent data mining assistant, based on the
synergistic combination of both declarative (Description
Logic) and procedural (SWRL Rules) ontology
knowledge in order to empower the non-specialist data
miner throughout the key phases of the CRISP-DM data
mining process.